采用逐次正交化法的最优分布式Kalman滤波器

为解决大系统中应用整体式Kalman滤波遇到的非实时性难题,本文提出一种能保持最优的分布式Kalman滤波计算方法——逐次正交化法。这是一种适合多微机并行计算的最优算法,确保滤波的“实时性”,优于一般次优分布式Kalman滤波器。     

羊毛精纺织物服用性能优选的多属性模糊决策

本文应用多属性目标决策的方法,评判不同规格毛织面料的"满意度",客观地提供一个重要的优选辅助依据。     

双层多目标规划若干问题的研究

研究了下层决策者无关联的双层多目标规划问题，在不同偏好意义下，给出了各自解的定义，讨论了线性双层多目标规划问题。     

结构优化中的混合变量应力约束近似方法

提出一种处理结构优化应力约束的新近似方法，以往一般直接对应力约束按设计变量近似，本文用近似内力间接近似应力约束以得到更高的近似质量，根据对内力和设计变量关系分析，提出了内力按混合变量一阶泰勒展开的高捏近似方法。近似优化问题用约束变尺度法求解，最后按出了几个典型例题。结果表明该方法简单，有效，可靠。     

基于参数化模型和遗传算法的复合材料加筋壁板结构选型优化研究

针对复合材料加筋壁板的结构优化选型问题,采用辅助层压板和添加极小弹性模量材料的复合材料加筋壁板有限元建模方法,应用PATRAN/NASTRAN的参数化建模功能和遗传算法相结合的复合材料加筋壁板的优化方法,对5种复合材料结构形式进行了从2000N/mm到6000N/mm压缩载荷下的结构优化分析。结果表明,当载荷小于4500N/mm时,最有效的加筋壁板结构型式为J型;当压缩载荷大于4500N/mm时,最有效的加筋壁板结构型式为I型。     

An improved approach for rainfall estimation over Indian summer monsoon region using Kalpana-1 data

In this paper, an improved Kalpana-1 infrared (IR) based rainfall estimation algorithm, specific to Indian summer monsoon region is presented. This algorithm comprises of two parts: (i) development of Kalpana-1 IR based rainfall estimation algorithm with improvement for orographic warm rain underestimation generally suffered by IR based rainfall estimation methods and (ii) cooling index to take care of the growth and decay of clouds and thereby improving the precipitation estimation.     

Application of improved active disturbance rejection control algorithm in tilt quad rotor

The Tilt Quad Rotor (TQR) has complex dynamics characteristics, especially in conversion mode. It is difficult to build the dynamic model of the TQR and the environmental factors have a great influence on it. To solve the problem of control in conversion mode of TQR, this paper carries out the design of the controller based on improved Active Disturbance Rejection Control (ADRC). According to the characteristics of flight in conversion mode, Tracking Differentiator (TD) with explicit model is used to solve the problem of multiple integrals when the system is high-order system. Extended State Observer (ESO) with Radial Basis Function (RBF) neural network is used to estimate and compensate for internal and external uncertainties, and the adaptive sliding mode control in Nonlinear State Error Feedback (NLSEF) is used to improve the response speed of the controller and reduce the parameters which should be tuned. Through the flight control simulation of the TQR, the validity and rationality of the control system are verified.     

再论和谐社会的构建——基于功能冲突论视阈

作为对二战后美国社会矛盾激化、社会动荡的回应,在对社会学家关于社会冲突的种种观点反思与发展的基础上,科塞建立了功能冲突论。科塞的功能冲突论由冲突正功能的发挥条件、冲突正功能的具体内容、社会安全阀制度等内容组成。功能冲突论启示我们,在我国构建和谐社会的过程中,要正视、分析社会矛盾、社会冲突,构建社会安全阀制度,消除社会冲突产生的社会土壤。     

Influence of TiB2 particles on machinability and machining parameter optimization of TiB2/Al MMCs

In situ formed TiB₂ particle reinforced aluminum matrix composites (TiB₂/Al MMCs) have some extraordinary properties which make them be a promising material for high performance aero-engine blade. Due to the influence of TiB₂ particles, the machinability is still a problem which restricts the application of TiB₂/Al MMCs. In order to meet the industrial requirements, the influence of TiB₂ particles on the machinability of TiB₂/Al MMCs was investigated experimentally. Moreover, the optimal machining conditions for this kind of MMCs were investigated in this study. The major conclusions are: (1) the machining force of TiB₂/Al MMCs is bigger than that of non-reinforced alloy and mainly controlled by feed rate; (2) the residual stress of TiB₂/Al MMCs is compressive while that of non-reinforced alloy is nearly neutral; (3) the surface roughness of TiB₂/Al MMCs is smaller than that of non-reinforced alloy under the same cutting speed, but reverse result was observed when the feed rate increased; (4) a multi-objective optimization model for surface roughness and material removal rate (MRR) was established, and a set of optimal parameter combinations of the machining was obtained. The results show a great difference from SiC particle reinforced MMCs and provide a useful guide for a better control of machining process of this material.     

基于自适应径向基网络的舰船RCS统计特征识别方法

文章采用舰船RCS频域起伏序列的均值、标准差为识别特征向量,利用提出的基于样本密度的自适应径向基网络,进行舰船分类识别研究。自适应径向基网络采用改进的自适应PSO方法估计样本密度最优邻域半径,实现径向基网络中心的自适应选择。改进的自适应PSO方法采用能反映样本聚类特点的BWP指标为适应度评价函数,采用快慢结合的高斯自适应惯性权重调节策略,提高了最优样本密度邻域半径的搜索速度和精度。实验结果表明,自适应径向基网络能自适应获得径向基网络最优识别率对应的RBF中心及其位置分布,减少了对建模人员经验的依赖,提高了反舰导弹对舰船类型的识别分类能力。